Bibliographic record
Abstract
Therapeutic angiogenesis/vasculogenesis holds promise for the cure of ischaemic disease. The approach postulates the manipulation of spontaneous healing response by supplementation of growth factors or transplantation of vascular progenitor cells. These supplements are intended to foster the formation of arterial collaterals and promote the regeneration of damaged tissues. Angiogenic factors are generally delivered in the form of recombinant proteins or by gene transfer using viral vectors. In addition, new non-viral methods are gaining importance for their safer profile. The association of growth factors with different biological activity might offer distinct advantages in terms of efficacy, yet combined approaches require further optimization. Alternatively, substances with pleiotropic activity might be considered, by virtue of their ability to target multiple mechanisms. For instance, some angiogenic factors not only stimulate the growth of arterioles and capillaries, but also inhibit vascular destabilization triggered by metabolic and oxidative stress. Transplantation of endothelial progenitor cells was recently proposed for the treatment of peripheral and myocardial ischaemia. Progenitor cells can be transplanted either without any preliminary conditioning or after ex vivo genetic manipulation. Delivery of genetically modified progenitor cells eliminates the drawback of immune response against viral vectors and makes feasible repeating the therapeutic procedure in case of injury recurrence. It is envisioned that these new approaches of regenerative medicine will open unprecedented opportunities for the care of life-threatening diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".